GenAI Insurance SME — Underwriting & Risk for AI Training

Obsidian; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Cincinnatus LLC is placing an Insurance SME at a leading AI lab in San Francisco to help evaluate AI outputs and ground them in underwriting expertise.

You will design tasks, write scoring rubrics, and collaborate with researchers to ensure high‑quality training data for foundation AI models.

Applicants should have 8+ years in insurance, experience evaluating LLM outputs, and be able to work ~35 hours/week during weekdays.

Qualifications

• 8+ years of dedicated professional experience in insurance at a top-tier organization.
• Hands-on experience evaluating LLM/AI outputs against rubrics or structured scoring criteria.
• Demonstrable career progression in underwriting leadership.
• Ability to engage reliably for at least 35 hours/week during weekdays.
• Strong verbal and written communication and problem-solving skills.

Responsibilities

• Guide research and engineering teams to close knowledge gaps in underwriting, claims, and risk assessment reasoning.
• Design domain-relevant insurance tasks and write accurate, well-reasoned solutions grounded in real underwriting/claims practice.
• Evaluate AI model outputs against structured rubrics and provide clear, written feedback on correctness, judgment, and reasoning quality.
• Develop and refine evaluation guidelines and scoring rubrics specific to insurance tasks.
• Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

Skills

Underwriting

Risk management

Claims evaluation

AI evaluation

Rubrics

Interpersonal skills

Communication

Job description

Cincinnatus LLC is placing an Insurance SME at a leading AI lab in San Francisco to help evaluate AI outputs and ground them in underwriting expertise.

You will design tasks, write scoring rubrics, and collaborate with researchers to ensure high‑quality training data for foundation AI models.

Applicants should have 8+ years in insurance, experience evaluating LLM outputs, and be able to work ~35 hours/week during weekdays.